Project Summary Lung cancer will account for 14% of all cancer diagnoses and remains the leading cause of cancer related death in men and women in the US and worldwide [1]. Despite decades of advances in tumor biology and understanding of the pathogenesis of disease, survival remains tethered to the early detection and prevention of tumor metastasis. We have learned that the failure of drug therapy is due to survival pathways of cells within the tumor that allow for not simply drug resistance, but for evading detection of our immune systems. Specifically, patients with EGFR-mutant NSCLC are now treated with targeted therapy, yet certain cells acquire drug resistance, yielding metastatic disease within a year. Early detection of disease is the single most important predictor of survival. However, there are still subsets of patients who undergo an R0 resection of Stage I disease, and go on to have metastatic disease. It is clinically critical to discern those patients who have this tumor biology. In our proposed study, we plan to utilize two important technological advancements to achieve our research goals, which have been developed and studied extensively by our lab. Circulating tumor cells (CTCs) are shed into the bloodstream from both primary and metastatic tumor implants. Studying these rare populations of cells will provide us important links between primary tumors and metastatic progression. We will utilize the third generation CTC-iChip, a highly efficient microfluidic based technology, to isolate these rare populations of circulating tumor cells (CTCs) from previously established EGFR-mutant mice xenografts [2,3]. Next, these cells will undergo single cell RNA sequencing to examine transcriptional expression profiles and explore intratumor heterogeneity. We have already demonstrated in pancreatic [4], breast [5], and prostate cancers [6] the ability of this technology to capture and study the transcriptome profiles of these rare cells. This proposal seeks to create a new model in lung cancer research, which would have direct clinical implications for human trials. In this study we seek to recapitulate in mice models, the behavior of clinical disease in EGFR-mutant lung cancer. We will utilize well-established EGFR mutant lung cancer models in order to perform a comprehensive analysis and validation of our model in humans. We hypothesize that mouse models will match that of our human experience, and that RNA expression levels of key driver mutations will reveal survival pathways to metastasis, correlate with tumor responsiveness to therapy, overall survival and allow for monitoring of drug response and new screening paradigms.